Motivation
I wanted to explore MLOps tooling outside of the Python ecosystem. Rust’s performance and reliability make it an interesting choice for building ML pipelines — so I built a gold price forecasting tool end-to-end in Rust, from data ingestion to a web-based prediction UI.
How It Works
The project uses a linear regression model trained on historical gold prices in INR. Given a date range, it fits the model on the historical data and extrapolates to generate future price forecasts.
Key components:
- Data pipeline — ingests and preprocesses historical gold price data
- Linear regression model — trained in Rust, outputs predicted prices over a user-defined forecast window
- Web UI — a dark-themed dashboard for visualizing price history and forecasts, with interactive date range controls
Demos
